How to Deploy Serverless Applications on AWS Lambda with Terraform

In the world of cloud computing, serverless architecture has gained significant traction due to its scalability, cost-effectiveness, and ease of use. AWS Lambda, Amazon's serverless computing service, allows developers to run code without provisioning or managing servers. In this article, we will dive deep into deploying serverless applications on AWS Lambda using Terraform, a powerful infrastructure as code (IaC) tool that simplifies the process of managing cloud resources.

Understanding AWS Lambda and Terraform

What is AWS Lambda?

AWS Lambda lets you run code in response to events, such as changes in data or system state. It automatically manages the compute resources for you, which means you can focus solely on writing your application code. The key benefits of using AWS Lambda include:

• Automatic Scaling: AWS Lambda automatically scales your applications by running code in response to each trigger.
• Pay-per-use Pricing: You only pay for the compute time you consume—there are no charges when your code isn't running.
• Support for Multiple Languages: AWS Lambda supports various programming languages, including Python, Node.js, Go, Java, and C#.

What is Terraform?

Terraform is an open-source tool created by HashiCorp that allows you to define your infrastructure using a high-level configuration language. It enables you to manage cloud services through code, which can be versioned, shared, and reused. Key features of Terraform include:

• Infrastructure as Code: Write infrastructure configurations in a declarative language.
• Execution Plans: Terraform generates an execution plan to show what will happen when you apply your changes.
• Resource Management: Manage resources across multiple providers, including AWS, Azure, and Google Cloud.

Use Cases for Serverless Applications

Serverless applications can serve a variety of use cases, including:

• Web Applications: Quickly deploy back-end services for web applications without managing servers.
• Data Processing: Use Lambda to process data streams in real-time, such as logs or IoT data.
• API Backends: Create RESTful APIs with AWS Lambda and API Gateway, allowing for easy integration and scalability.
• Scheduled Tasks: Run periodic tasks without worrying about underlying infrastructure.

Deploying a Serverless Application on AWS Lambda with Terraform

Now that we have a fundamental understanding of AWS Lambda and Terraform, let's walk through the process of deploying a simple serverless application.

Step 1: Install Required Tools

Before we begin, ensure you have the following tools installed on your local machine:

• Terraform: Download and install from Terraform's official website.
• AWS CLI: Install and configure the AWS CLI with your AWS credentials.
• Node.js: Ensure Node.js is installed to run our sample application.

Step 2: Set Up Your Project Structure

Create a new directory for your project:

mkdir lambda-terraform-example
cd lambda-terraform-example

Inside this directory, create the following structure:

lambda-terraform-example/
├── main.tf
├── variables.tf
├── lambda/
│   └── index.js

Step 3: Write Your Lambda Function

In the lambda/index.js file, create a simple Lambda function:

exports.handler = async (event) => {
    const response = {
        statusCode: 200,
        body: JSON.stringify('Hello from AWS Lambda!'),
    };
    return response;
};

Step 4: Create the Terraform Configuration

Now, let's set up the Terraform configuration files.

4.1 main.tf

In main.tf, define your provider and Lambda function:

provider "aws" {
  region = "us-east-1"
}

resource "aws_lambda_function" "my_lambda" {
  function_name = "MyLambdaFunction"

  s3_bucket = aws_s3_bucket.lambda_bucket.bucket
  s3_key    = aws_s3_bucket_object.lambda_zip.key

  handler = "index.handler"
  runtime = "nodejs14.x"

  role = aws_iam_role.lambda_exec.arn
}

resource "aws_iam_role" "lambda_exec" {
  name = "lambda_exec_role"

  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [
      {
        Action = "sts:AssumeRole"
        Effect = "Allow"
        Principal = {
          Service = "lambda.amazonaws.com"
        }
      },
    ]
  })
}

resource "aws_s3_bucket" "lambda_bucket" {
  bucket = "my-lambda-bucket-${random_string.bucket_suffix.result}"
}

resource "aws_s3_bucket_object" "lambda_zip" {
  bucket = aws_s3_bucket.lambda_bucket.bucket
  key    = "lambda.zip"
  source = "lambda/index.js"  # Use a zip file in a real-world scenario
}

4.2 variables.tf

Add any necessary variables in variables.tf:

variable "aws_region" {
  description = "The AWS region to deploy resources"
  default     = "us-east-1"
}

Step 5: Initialize and Deploy with Terraform

Now, it’s time to deploy our Lambda function using Terraform.

1. Initialize Terraform:

terraform init

1. Format and Validate Your Configuration:

terraform fmt
terraform validate

1. Plan the Deployment:

terraform plan

1. Apply the Changes:

terraform apply

When prompted, type yes to confirm creating the resources. Terraform will create the specified AWS Lambda function and associated resources.

Step 6: Testing Your Lambda Function

Once deployed, you can test your Lambda function through the AWS Management Console or by using the AWS CLI:

aws lambda invoke --function-name MyLambdaFunction output.txt
cat output.txt

You should see the message: Hello from AWS Lambda!.

Troubleshooting Common Issues

• Permissions Errors: Ensure your IAM role has the necessary permissions to execute Lambda functions and access other AWS resources.
• Deployment Errors: Check for any errors in the Terraform output. Ensure that your S3 bucket is unique and complies with AWS naming conventions.
• Code Errors: Review your Lambda function code for issues. Use CloudWatch logs to debug runtime errors.

Conclusion

Deploying serverless applications using AWS Lambda and Terraform can significantly streamline your development workflow. By leveraging infrastructure as code, you can easily manage, update, and scale your applications without the overhead of traditional server management. With the steps outlined in this article, you're well on your way to building robust serverless applications that can meet your business needs. Happy coding!